Machine vision systems include one or more cameras to capture images. The captured images are used in various applications, such as inspection of items, process control, security, smart city, etc. The images captured by the camera are transmitted to a computer system for processing and/or analyzing. In conventional machine vision systems, the computer system that receives the images from the camera is separate and distinct from the camera.
In some conventional machine vision systems, the computer system is typically in proximity to the camera (e.g., in a room near the camera). This can be referred to as edge computing. Typically, the environment for machine vision systems introduces a host of factors that can negatively affect the functionality of the computer system, such as heat, dust, water, bugs, and so on. As a result, there is increased expense and burden to protect the computer system from the environment. Moreover, the computer system may fail due to extended exposure to the environment.
In other conventional machine vision systems, the computer system is a cloud-based computing system where image data is transmitted over a network. The image data is then processed using the cloud-based computing system. This typically utilizes a network connection that is capable of handling a large amount of data to be consistently transmitted. However, if the network connection fails (or has decreased bandwidth or intermittent connection), then the machine vision system may be rendered useless.
Moreover, when a camera is connected over a network, the image information captured by the camera is compressed and subsequently transmitted over the network. As a result, the image information is lost or reduced. The image information is dynamic range, temporal and spatial detail, resolution, etc.